Measurement of helicity flux density using the eddy-current diagnostic system in Keda Torus eXperiment device
Bibliographic record
Abstract
The flux of magnetic helicity characterizes how the topology of a magnetic field changes and helicity and its transport play essential roles in plasma equilibrium and instabilities in the reversed-field pinch (RFP) device configuration. Used to suppress magnetohydrodynamic instabilities effectively, the stabilizing conducting shell located at the boundary of an RFP device is always characterized by an eddy-current distribution that evolves rapidly with time. After measuring and analyzing the eddy currents on this stabilizing shell during tokamak discharges in the Keda Torus eXperiment device, the distributions of multiple physical quantities on the shell are obtained, including the magnetic fields, eddy currents, and electric fields. An experimental technique for measuring helicity flux density is demonstrated, combined with eddy-current diagnosis and these physical vectors on the boundary. How the magnetic and current helicity flux densities evolve is given by a feasible mathematical analysis, and data suggest that the plasma mediates both the generation and transport of magnetic helicity during the discharge. The experimental results of the distribution of the magnetic helicity flux densities (MHFDs) due to the instability on the boundary are given, and the average of these MHFDs over the whole boundary surface is far less than the maximum value of the MHFDs. In addition, the results of current helicity flux densities on the boundary are also presented.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".